My time working at the World Bank included several results-based financing projects (RBF). In a nutshell, RBF ties payments to the independent verification of results. Sometimes it’s called Payment by Results (PbR). In many ways it’s just another case of aid conditionality.
I was a little skeptical for sure (okay, sometimes a lot). Nevertheless, I paddled along—expressing my doubts but trying to make the best of donor-driven mandates to proliferate RBF all over the development aid space.
Part of me liked (and still likes) the idea of RBF because it seems less prescriptive, less solutions-driven. Local communities can do what they want, and adopt appropriate technologies for their particular contexts so long as results are achieved. At the same time, part of me felt like we—the aid agencies—were micromanaging and making people jump through hoops to do a little dance for us, simultaneously completely absolving ourselves of responsibility to actually do anything.
But what really gets me about RBF (or PbR), is this point from Duncan Green’s recent blog:
“…What exactly are these results and who are we measuring them for? PbR pushes project implementation even further towards ‘upwards accountability’- mainly developing country governments collecting and processing results (which can be an expensive business) in order to satisfy aid donors and their political backers and tax payers. To what extent are those results any use for a) learning and improving or b) increasing accountability where it is really lacking – downwards to poor people and communities?”
When we talk about accountability for RBF, we often think of upward accountability but not of downwards accountability. In designing RBF projects, the indicators to be met are commonly set by the aid agencies with little consultation with the communities who are affected and have to successfully perform in order to receive the incentive payments.
Moreover, we think of accountability in a very one-dimensional way: records, indicators, or numbers about performance. Accountability is a policing mechanism to make sure what’s supposed to get done, gets done. Accountability, in this sense, is about accounting and what some are calling “thin” accountability.
What if we focused on thick instead of thin accountability? The account in thick accountability refers to the stories and feedback people provide to help explain what they do and why. Thick accountability allows you to not just superficially evaluate results, but to more meaningfully learn why and how some things are done or not.
How can we merge RBF and a learning (vs. accountability) agenda? How can we merge RBF and more rapid-cycle feedback to help communities get to the results they care about? Learning, after all, is the only way we can really improve.